docstr: Registers dataset sources defined as Python entrypoints. For reference, see
  https://mlflow.org/docs/latest/plugins.html#defining-a-plugin.
docstr_tok: ["Registers","dataset","sources","defined","as","Python","entrypoints",".","For","reference",",","see","https",":","\/\/mlflow.org\/docs\/latest\/plugins.html","#","defining-a-plugin","."]
code: def register_entrypoints(self):
      """
      Registers dataset sources defined as Python entrypoints. For reference, see
      https://mlflow.org/docs/latest/plugins.html#defining-a-plugin.
      """
      for entrypoint in entrypoints.get_group_all(
          "mlflow.dataset_source"
      ):
          try:
              self.register(entrypoint.load())
          except (AttributeError, ImportError) as exc:
              warnings.warn(
                  f"Failure attempting to register dataset source with source type"
                  f' "{entrypoint.source_type}": {exc}',
                  stacklevel=2,
              )
  
file_path: mlflow/mlflow/data/dataset_source_registry.py
imports: import warnings
  from typing import Any, List, Optional
  import entrypoints
  from mlflow.data.artifact_dataset_sources import register_artifact_dataset_sources
  from mlflow.data.dataset_source import DatasetSource
  from mlflow.data.http_dataset_source import HTTPDatasetSource
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import RESOURCE_DOES_NOT_EXIST
label_desc: Use image node_id 3 for calling the DatasetSourceRegistry obj's underlying member method code with example usage: obj.register_entrypoints() without return types